Multi-target electric vehicle charging network planning method

A charging network and electric vehicle technology, applied in multi-objective optimization, forecasting, resources, etc., can solve the problem of not considering the average charging distance and charging network construction costs at the same time, and achieve the effect of reducing construction costs and optimizing construction locations

Inactive Publication Date: 2022-04-12
NANTONG UNIVERSITY
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Problems solved by technology

However, the existing methods do not consider the average charging distance an...

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  • Multi-target electric vehicle charging network planning method
  • Multi-target electric vehicle charging network planning method
  • Multi-target electric vehicle charging network planning method

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[0080] The present invention will be further explained below in conjunction with the accompanying drawings, so that those skilled in the art can understand the present invention more deeply and can implement it smoothly, but the following reference examples are only used to explain the present invention, not as a limitation of the present invention.

[0081] An embodiment of the present invention provides a multi-objective electric vehicle charging network planning method, including the following steps:

[0082] S1: Set planning boundary conditions. The planning boundary conditions include: traffic network topology and parameters, charging station candidate addresses, charging station construction costs of each candidate site, total number of charging station construction, charging mileage threshold and confidence level ; The candidate addresses of the charging stations are all transportation nodes in the transportation network.

[0083] S2: Establish a multi-objective chance-...

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Abstract

The invention relates to the technical field of electric vehicle charging networks, and discloses a multi-target electric vehicle charging network planning method. Comprising the steps that S1, planning boundary conditions are given; s2, establishing a charging network multi-target opportunity constraint planning model which considers the shortest average charging driving distance of the electric vehicle and the lowest construction cost of the charging network at the same time; s3, designing a chromosome coding scheme and crossover and mutation operators, solving the charging network multi-target opportunity constraint programming model by adopting a non-dominated genetic algorithm based on a feasibility rule, and giving a Pareto solution set of the charging network multi-target opportunity constraint programming model; and S4, starting from a solution with the lowest investment cost in the Pareto solution set, determining an optimal charging network planning scheme according to a marginal investment income maximum principle. The average driving distance from the electric vehicle to the charging station and the construction cost of the charging network are reduced.

Description

technical field [0001] The invention relates to the technical field of electric vehicle charging network planning, in particular to a multi-objective electric vehicle charging network planning method. Background technique [0002] In recent years, with the excessive use of fossil energy and the increasing environmental pollution, the development of green vehicles represented by electric vehicles has become the consensus of all countries in the world. my country has also formulated a series of policies to encourage the development of the electric vehicle industry. At this stage, electric vehicles mainly supplement electric energy from the grid, and charging stations are one of their important charging places. A well-structured electric vehicle charging network can significantly improve the convenience of charging for car owners, stimulate the whole society's willingness to purchase electric vehicles, and promote the further development of the electric vehicle industry. [00...

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Application Information

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IPC IPC(8): G06F30/15G06F30/18G06F30/27G06Q10/04G06Q10/06G06Q50/06G06Q50/30G06N3/12G06F111/04G06F111/06G06F111/08
Inventor 张新松李大祥董健郭傲伟赵至哲高宁宇张齐
Owner NANTONG UNIVERSITY
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